References
Fung, G., Mangasarian, O.L., Shavlik, J.: Knowledge-based support vector machine classifiers. In: Becker, S., Thrun, S., Obermayer, K. (eds.) Advances in Neural Information Processing Systems 15, pp. 521–528. MIT Press, Cambridge (2003). ftp://ftp.cs.wisc.edu/pub/dmi/tech-reports/01-09.ps
Mangasarian, O.L.: Linear and nonlinear separation of patterns by linear programming. Oper. Res. 13, 444–452 (1965)
Mangasarian, O.L.: Minimum-support solutions of polyhedral concave programs. Optimization 45, 149–162 (1999). ftp://ftp.cs.wisc.edu/math-prog/tech-reports/97-05.ps
Mangasarian, O.L.: Generalized support vector machines. In: Smola, A., Bartlett, P., Schölkopf, B., Schuurmans, D. (eds.) Advances in Large Margin Classifiers, pp. 135–146. MIT Press, Cambridge (2000). ftp://ftp.cs.wisc.edu/math-prog/tech-reports/98-14.ps
Mangasarian, O.L.: Knowledge-based linear programming. SIAM J. Optim. 15, 375–382 (2005). ftp://ftp.cs.wisc.edu/pub/dmi/tech-reports/03-04.ps
Mangasarian, O.L.: Absolute value equation solution via concave minimization. Optim. Lett. 1(1), 3–8 (2007). ftp://ftp.cs.wisc.edu/pub/dmi/tech-reports/06-02.pdf
Mangasarian, O.L.: Absolute value programming. Comput. Optim. Appl. 36(1), 43–53 (2007). ftp://ftp.cs.wisc.edu/pub/dmi/tech-reports/05-04.ps
Mangasarian, O.L.: A generalized Newton method for absolute value equations. Technical Report 08-01, Data Mining Institute, Computer Sciences Department, University of Wisconsin (May 2008). ftp://ftp.cs.wisc.edu/pub/dmi/tech-reports/08-01.pdf. Optim. Lett. (to appear)
Mangasarian, O.L., Meyer, R.R.: Absolute value equations. Linear Algebra Appl. 419, 359–367 (2006). ftp://ftp.cs.wisc.edu/pub/dmi/tech-reports/05-06.pdf
Mangasarian, O.L., Wild, E.W.: Nonlinear knowledge-based classification. Technical Report 06-04, Data Mining Institute, Computer Sciences Department, University of Wisconsin, Madison, Wisconsin (August 2006). ftp://ftp.cs.wisc.edu/pub/dmi/tech-reports/06-04.pdf, IEEE Trans. Knowl. Data Eng. (to appear)
Mangasarian, O.L., Wild, E.W.: Privacy-preserving classification of horizontally partitioned data via random kernels. Technical Report 07-03, Data Mining Institute, Computer Sciences Department, University of Wisconsin, Madison, Wisconsin (November 2007). Proceedings of the 2008 International Conference on Data Mining, DMIN08, Las Vegas July 2008, Volume II, pp. 473–479, R. Stahlbock, S.V. Crone and S. Lessman, Editors
Mangasarian, O.L., Wild, E.W.: Nonlinear knowledge in kernel machines. In: Pardalos, P.M., Hansen, P. (eds.) Data Mining and Mathematical Programming. Centre de Recherches Mathématiques Montréal Proceedings and & Lecture Notes, pp. 181–198. American Mathematical Society, Providence (2008). ftp://ftp.cs.wisc.edu/pub/dmi/tech-reports/06-06.pdf
Mangasarian, O.L., Wild, E.W., Fung, G.M.: Proximal knowledge-based classification. Technical Report 06-05, Data Mining Institute, Computer Sciences Department, University of Wisconsin, Madison, Wisconsin (November 2006). ftp://ftp.cs.wisc.edu/pub/dmi/tech-reports/06-05.pdf. Stat. Anal. Data Mining (to appear)
Mangasarian, O.L., Wild, E.W., Fung, G.M.: Privacy-preserving classification of vertically partitioned data via random kernels. Technical Report 07-02, Data Mining Institute, Computer Sciences Department, University of Wisconsin, Madison, Wisconsin (September 2007). ACM Trans. Knowl. Discov. Data (TKDD) (to appear)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hager, W.W. COAP 2007 Best Paper Award. Comput Optim Appl 41, 147–149 (2008). https://doi.org/10.1007/s10589-008-9203-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10589-008-9203-8